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It's a wonderful thing when people make interesting data sets available to the public. When Thomas Jones wrote a paper in Econometrics about the growth of US retail giant Walmart, he made the data he collected about every Walmart store opening in history (location and date) available to the public. Since then, several people have used different techniques to visualize the data. 

You've probably heard (or seen in TV shows) how the unique pattern of rifling in a gunbarrel generates forensic evidence: microscopic scoring on the bullets left at the scene of the crime can be linked to the shooter by matching the marks to the firearm.

The most recent edition of the Revolution Newsletter is out. The news section is below, and you can read the full August edition (with highlights from this blog and community events) online. You can subscribe to the Revolution Newsletter to get it monthly via email. used the R language and data from the National Snow and Ice Data Center to create this chart showing the extent of Arctic sea-ice in each year since satellite observations began in 1978, and the current extent of ice coverage (in red).

Two significant R community milestones were achieved over the weekend.

Anyone who has dogs knows that they can get into a mighty amount of mischief. But I'd never have guessed all the different types of mischief that dogs can get into, until I came across the Dog Shaming website. Here you'll find pictures of guilty-looking dogs (and a few cats) with notes describing their nefarious deeds, like "I locked myself in the car. They had to call a locksmith", and "I hid meat in the couch". I'm glad our dogs aren't the only ones with shameful behaviour!

National Institute for Occupational Safety and Health study, published in March, found that professional American football (NFL) players lived longer, on average, than similar "mere mortals" in the general population.

A big thank-you to all the R users out there who voted for Revolution R Enterprise in DataWeek Awards.

If you're writing C++ code and want to generate random numbers, you might not be aware that R provides an API to call the R RNG functionality directly. The Rcpp package's "syntactic sugar" feature makes this process easier, by automating the process of translating a subset of ordinary R code into compiled C++ code.

People use the R language every day to create the elements of reports: tables, charts, analyses, and forecasts. But assembling all of that information into a print-ready document laid out with text can a hassle. You can cut-and-paste all of the elements into Word, but then what do you do when the data file gets updated at the last minute? (Answer: you have to re-run all the R code and go through the whole cut-and-paste process again.